A report on zero rating by the Federal Communications Commission just a week and a half before the inauguration of Donald Trump said that zero rating for ISPs and mobile network operators violates net neutrality rules. “Zero-rated” applications do not count toward data caps or usage allowance imposed by internet service providers. Forbes staff writer Parmy Olson called the report “too little too late”.
Zero rating has come under fire from many quarters. “While network capacity could become a problem if zero-rated offerings truly take off,” writes Colin Gibbs in a review of 2016 for Fierce Wireless, “the biggest challenge to the model has been claims that it’s a threat to net neutrality rules.” Last year, Verizon began offering zero rated video streaming though NFL Mobile app.
Keeping the Net Neutral
The idea of net neutrality is that everything on the internet should be treated openly and fairly. Net neutrality prohibits blocking of sites by ISPs. It prohibits throttling: ISPs should not slow down or speed up content for different services. It calls for increased transparency and prohibits paid prioritization of traffic. Before the recent FCC report, sponsored data plans – plans with zero rating – were to be judged by the agency on a case-by-case basis.
Zero Rating for ISPs and Mobile Network Services
Facebook offers free internet access to underdeveloped countries with curated content. According to Internet.org, “Free Basics by Facebook provides people with access to basic websites for free – like news, job postings, health and education information, and communication tools like Facebook.” The motto of the service is “Connecting the World”.
A number of mobile network providers have taken up the practice. The first to try zero rating was T-Online with their Music Freedom offering in 2014. They followed that up with a video service called Binge On. Verizon came up with their own mobile video service called Go90. Perhaps the most aggressive has been AT&T’s partnership with DirecTV. Virgin Mobile 4G Plans Now Allow Free Zero Rated Data Use on Twitter.
Presenting the case against zero rating for ISPs and mobile network operators services, the young Mike Egan stated articulately in a YouTube video: “Zero rating isn’t about giving online services or online creators a chance. It’s about mobile carriers finding a loophole so that they can keep you even more locked into what easily becomes their new media ecosystem.”
He says that “certain services are privileged over others” and that it is one of the best ways to “kill a free and open internet”. Egan and others like him are upset, and he talks in terms of “the oppressor” versus “the oppressed”. The Federalist Society takes a different view. In their YouTube video about zero rating, they compare it to getting free samples of ice cream. “This is a way to increase the adoption of the internet,” the spokeswoman says. “All that zero rating is doing is helping to increase the competition and expanding the user choice.”
The Less Regulated Road Ahead
The “too little too late” remark of the Forbes staffer is all about the new political realities in America. Despite the recent pronouncement again zero rating by the FCC, chances are the practice will continue unabated. President Trump has vowed to cut government regulations by 75%, and the new FCC chairman Ajit Pai will likely tamp down any opposition to zero rating for ISPs and mobile network operators.
A blog post from CCS Insight says, “Mr. Pai had opposed government intervention in the telecommunications market and has been an open critic of an FCC report disapproving of zero-rating data, also known as toll-free data….” The blogger goes on to say that there will certainly be a rise in the number of toll-free data offers.
Conclusion on Zero Rating for ISPs and Mobile Network Operators Services
Many are concerned about the potential loss of internet freedom with zero rating. As Egan put it, “It’s a war for the future of our media landscape.” How that war plays out when deregulation sets in remains to be seen. Neutrality is a hard thing to maintain. What are your ideas on zero rating? Does your network provider bundle any of these services? How do you think it will affect the future of the internet? Please add your comments below.
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IoT medical devices transforming healthcare by changing every aspect of our social and professional lives as billions of pervasive devices enable the acquisition of timely and accurate information about our personal context, the data gathering transforms what doctors can do with actionable knowledge.
The healthcare sector provides an excellent example of the way in which the future billions of IoT devices will introduce disruptive transformation and new paradigms. In an era where population is aging and incidents of chronic diseases are proliferating, healthcare solution providers are increasingly looking into internet connected devices for remote monitoring of elderly and patients’ conditions.
This remote monitoring facilitates preemptive medical interventions, while at the same time increasing the patients’ independence, reducing hospitalization needs and alleviating pressures on the healthcare system.
One of the most prominent classes of IoT Medical Devices transforming healthcare today is wearable devices, which are personalized and provide rich and real-time information about an individual’s healthcare related context, such as heart rates, activity patterns, blood pressure or adherence to medication schedules.
Wearable devices play an instrumental role in monitoring patients’ diseases and recovery state, as well as adherence to prescribed practices and medication. A large number of relevant wearable devices are already available in the market such as activity trackers, smartwatches (e.g., Apple or Garmin Watches), pedometers, sleep apnea detector and smart pills (e.g., AdhereTech’s smart wireless pill bottle).
Implant IoT Medical Devices Transforming Healthcare
A less widely known class of wearable IoT medical devices transforming healthcare are implant devices, i.e. devices that are placed inside or on the surface of the human body. The concept of such devices has been around for several years prior to the rise of the IoT paradigm, as prosthetics that were destined to replace missing body parts or even to provide support to organs and tissues.
Therefore, implants were typically made from skin, bone and other body tissues, or from materials (e.g., metal, plastic or ceramic materials). While the distinguishing line between conventional IoT medical devices and wearable / implant devices can sometimes be blurred, we consider as implant medical devices those attached to the skin or placed inside the human body, instead of devices simply worn by the patient.
Impressive examples of implant devices are: (i) Brain implant devices (i.e. electrodes along with a battery empowered devices) used to manipulate the brain and alleviate chronic pain, depression or even schizophrenia; (ii) Electronic chips implanted at the back of the retina in the eye, in order to help sight restoration.
With the advent of IoT medical devices transforming healthcare, implant devices can also become connected and deliver information to cloud computing infrastructures and other applications. In this way, they can become part of the IoT infrastructure and enable the transmission of medical data from the patient to the practitioner on a regular basis. Moreover, with IoT implants patients no longer need to visit their doctor in order download data from their device or even in order to configure the operation of the implant device.
For example, by enhancing devices such as the electronic chip for vision restoration (outlined above) with a small handheld wireless power supply, one can adjust the sensitivity, contrast and frequency as needed in order to yield optimal performance of the device for different environmental settings (e.g., lighting conditions).
Risks and Challenges with IoT Medical Devices Transforming Healthcare
Despite their benefits, the adoption of implant IoT medical devices is still in its infancy. One of the main reasons is that the development and deployment of implants is associated with several challenges and risks. In particular, implants are associated with surgical risks concerning their placement and removal processes. Although generally safe, these processes could lead to infections or even implant failures, which makes patients reluctant to adopt them. Moreover, several patients have reported allergies and reactions to the materials comprising the implant devices.
Beyond these adoption challenges, there are also IoT technological challenges associated with the need to understand and optimize the placement and operation of the device. For example, there is a need to optimize radio communications between the implanted device and the receiving devices where the information of the implant is destined.
In this respect, low power operation is very important as a result of the need to economize on power capacity, while at the same time complying with applicable laws and regulations, including security and safety regulations.
From a technology viewpoint, implant solutions have to resolve trade-offs associated with efficiency and accuracy against antenna size, power use, operating bandwidth and materials costs. Moreover, implant devices should be appropriate for various body and skin morphologies, while at the same time offering security and data protection features that render them immune to malicious parties that may attempt to compromise their operation.
The above-listed factors render the design of cost-effective implants that adhere to regulations and optimize their operation very challenging. In order to alleviate these challenges, vendors and integrators of IoT implants resort to simulation. Simulation is an ideal tool for modelling the operation of the device and understanding its communication with the body and other devices of the surrounding environment such as gateways or even other implant devices.
Furthermore, vendors are implementing services that aim at increasing the operational efficiency of the devices, such as preventive or predictive maintenance of the device, as well as remote diagnostics and software upgrades (e.g., remote patching).
The last batch of challenges concerns the important business issues with IoT medical devices transforming healthcare, especially implants, which are not confined to selling devices. Rather, it is about innovating digitally and offering a whole range of services as part of the device’s industry ecosystem. Specifically, vendors and integrators of IoT implants need to find novel ways and business models for sharing their data with healthcare services providers and other stakeholders, while at the same time creating new value chains in collaboration with other device vendors, health professionals, home care services providers and other business actors.
The evolution of IoT medical devices transforming healthcare with implants will gradually signal a shift from the offering of an optimal IoT device to the offering of a pool of optimized and personalized healthcare services that will be built by the device’s industry ecosystem. Implant IoT medical devices are here and expected to play a significant role in the on-going IoT-driven transformation of the healthcare landscape. Stay tuned!
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It will be part of a “natural evolution of existing infrastructures” bringing greater efficiency and lower costs. But the key will be the creation of new services. “NFV in 2017 will be driven by services such as VoLTE, Carrier Cloud, Wi-Fi calling, service chaining, resource sharing and network slicing.”
Network Function Virtualization, aka NFV, was introduced to the world through a white paper that was delivered at the 2012 SDN and OpenFlow World Congress. Authors from thirteen different telecom providers contributed to the work. The paper highlighted several benefits of NFV, including reduced equipment costs, lower power consumption, faster time to market, scalability of services, and vendor interoperability.
The traditional approach to networking involved the dispatch of personnel, either to the data center or to the customer premises, to install the physical devices and cabling required to make the network services function. This sometimes involved a number of “truck rolls” until the network appliance was fully operational. But an implementation that might have taken weeks or even months through the traditional method might only take a few minutes with Network Function Virtualization.
Common appliances that can be replaced by virtualized network functions (VNFs) in the NFV architecture include routers, firewalls, switches, load balancers, and media servers. Instead of physical installs, Network Function Virtualization software can be used to simply “spin out” new services as needed. As traffic volume increases, the system may automatically create VNFs to meet the demand.
When things slow down, the infrastructure will automatically be reduced. Malfunctioning virtual devices will be detected and traffic will be rerouted through a new VNF created just for that purpose.
Replacing infrastructure is fine, but the real potential is in the expanding service portfolio of the NFV architecture. “By enabling service chaining and resource sharing,” says Northstream, “NFV allows operators to deliver network services to customers and enterprises through software instead of dedicated hardware devices. This represents a major step towards meeting the new demands of industry verticals that are just around the corner.”
Network Function Virtualization deployment is not without its challenges.
Yue believes that the biggest issue telecom companies need to deal with is orchestration, the automatic deployment of resources in the cloud. Trying to bring things together is “still very targeted and piecemeal”. Providers seem to be in a rush to bring services to market. “Really to get orchestration and everything right,” says Yue, “you need to have all these tiny projects come together in one big cohesive unit, and I don’t think we’re there yet.” Real time and automation are the key words, according to RCR Wireless editor Dan Meyer. For Frank Yue, the keys are agility and elasticity, terms associated with cloud computing.
Another major challenge is security. How do you maintain the privacy and integrity of your data across the cloud infrastructure? Industry standards have a bearing on security. Yue calls the situation a “big administrative mess”. Without proper standardization, particularly in multi-tenant environments, the potential for security breaches remains.
Network Function Virtualization Standards
One standards body, the European Telecommunications Standards Institute (ETSI), announced NVF Release 2 on September 27, 2016. The statement includes remarks from Telefonica’s Diego Lopez, the newly appointed Chairman of ETSI NFV ISG: “This represents another major step towards our objective of defining a comprehensive set of specifications that will facilitate the deployment of Network Function Virtualization throughout the telecommunication industry, with significant benefits being subsequently derived in many interrelated sectors.” Lopez says that the ETSI NFV Architectural Framework will form the basis for the security, reliability, and integration of NFV going forward.
How quickly will NFV revolutionize the networks of the world? That remains to be seen. It’s being looked at as a potential framework for 5G mobile deployments. Will service chaining fueled by NFV resources make large-scale network installations a simple point-and-click operation? How will Network Function Virtualization be used in the development of self-healing networks? What other innovations await us in the field of network virtualization? Get ready, because the virtualized future everyone dreamed about is well-nigh upon us.
Does your company plan to deploy NFV any time soon? What do you think about this new technology? How do you think it will affect telecom companies and their customers in the next few years? Please share your comments on Network Function Virtualization below.
Expanding NPV services for MNOs
Tier 1 and Tier 2 mobile network operators are expanding their 4G services as it is at least 5+ years before 5G networks are ready for early deployment. ARPU, expanding data services, lowering power consumption – these are all needed to be competitive and maintain a healthy profit ratio. If you require an expertise recruitment team to fill a key sales or engineering role or perhaps product management or a strategic leader, you can rely upon Nextgen Executive Search to not only meet, but exceed your expectations in delivering a candidate shortlist that is ideal for new hires. Click the image below for more information on our mobile network, digital media, telecom services, and wireless connectivity recruitment and to contact us directly.
IoT Recruiting – does your search firm deliver results?
IoT recruiting where a lot of recruiting firms out there – contingency based, RPOs, and retained search firms claim they can deliver results. You have the need to find the right candidate for a key senior executive or functional leadership role. Or you need a key sales, business development, or engineering professional?
The IoT recruiting team of NextGen Global Executive Search has 30+ years experience working for clients large and small in mobile networks, embedded wireless, IoT data and devices, industrial IoT applications and platforms, blockchains, agriculture, IoT consumer product goods wearables in sports, business, and fitness, as well as artificial intelligence and robotics.
IOT Recruiting that Delivers Results
NextGen has successfully recruited CEOs, CTOs, VPs and Directors in embedded wireless, ecosystem partnership development, firmware development, and network design for IoT operators, semiconductor and device manufacturers, and wireless sensors. Reach out to NextGen for your IoT recruiting needs. NextGen has 30+ years experience recruiting for mobile network operators, cellular infrastructure vendors, and wireless semiconductor device manufacturers. As 4G gets ready to evolve into 5G, both industrial IoT continues to grow and consumers will realize the benefits of Internet of Things connected to everything from smart homes with smart appliances to security to energy savings.
Smart Objects: Blending AI into the Internet of Things
It’s been more than a decade since the time when the number of internet-connected devices exceeded the number of people on the planet. This milestone signaled the emergence and rise of the Internet of Things (IoT) paradigm, smart objects, which empowered a whole new range of applications that leverage data and services from the billions of connected devices. Nowadays IoT applications are disrupting entire sectors in both consumer and industrial settings, including manufacturing, energy, healthcare, transport, public infrastructures and smart cities.
Evolution of IoT Deployments
During this past decade IoT applications have evolved in terms of size, scale and sophistication. Early IoT deployments involved the deployment of tens or hundreds of sensors, wireless sensor networks and RFID (Radio Frequency Identification) systems in small to medium scale deployments within an organization. Moreover, they were mostly focused on data collection and processing with quite limited intelligence. Typical examples include early building management systems that used sensors to optimize resource usage, as well as traceability applications in RFID-enabled supply chains.
Over the years, these deployments have given their place to scalable and more dynamic IoT systems involving many thousands of IoT devices of different types known as smart objects. One of the main characteristic of state-of-the-art systems is their integration with cloud computing infrastructures, which allows IoT applications to take advantage of the capacity and quality of service of the cloud. Furthermore, state of the art systems tends to be more intelligent, as they can automatically identify and learn the status of their surrounding environment to adapt their behavior accordingly. For example, modern smart building applications are able to automatically learn and anticipate resource usage patterns, which makes them more efficient than conventional building management systems.
Overall, we can distinguish the following two phases of IoT development:
Phase 1 (2005-2010) – Monolithic IoT systems: This phase entailed the development and deployment of systems with limited scalability, which used some sort of IoT middleware (e.g., TinyOS, MQTT) to coordinate some tens or hundreds of sensors and IoT devices.
Phase 2 (2011-2016) – Cloud-based IoT systems: This period is characterized by the integration and convergence between IoT and cloud computing, which enabled the delivery of IoT applications based on utility-based models such as Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). During this phase major IT vendors such as Amazon, Microsoft and IBM have established their own IoT platforms and ecosystems based on their legacy cloud computing infrastructures. The latter have alleviated the scalability limitations of earlier IoT deployments, which provided opportunities for cost-effective deployments. At the same time the wave of BigData technologies have opened new horizons in the ability of IoT applications to implement data-driven intelligence functionalities.
AI: The Dawn of a new era for Smart Objects using IoT applications
Despite their scalability and intelligence, most IoT deployments tend to be passive with only limited interactions with the physical world. This is a serious set-back to realizing the multi-trillion value potential of IoT in the next decade, as a great deal of IoT’s business value is expected to stem from real-time actuation and control functionalities that will intelligently change the status of the physical world.
In order to enable these functionalities we are recently witnessing the rise and proliferation of IoT applications that take advantage of Artificial Intelligence and Smart Objects. Smart objects are characterized by their ability to execute application logic in a semi-autonomous fashion that is decoupled from the centralized cloud. In this way, they are able to reason over their surrounding environments and take optimal decisions that are not necessarily subject to central control.
Therefore, smart objects can act without the need of being always connected to the cloud. However, they can conveniently connect to the cloud when needed, in order to exchange information with other passive objects, including information about their state and the status of the surrounding environment. Prominent examples of smart objects follow:
Socially assistive robots, which provide coaching or assistance to special user groups such as elderly with motor problems and children with disabilities.
Industrial robots, which complete laborious tasks (e.g., picking and packing) in warehouses, manufacturing shop floors and energy plants.
Smart machines, which predict and anticipate their own failure modes, while at the same time scheduling autonomously relevant maintenance and repair actions (e.g., ordering of spare parts, scheduling technicians visits).
Connected vehicles, which collect and exchange information about their driving context with other vehicles, pedestrians and the road infrastructure, as a means of optimizing routes and increasing safety.
Self-driving cars, which will drive autonomously with superior efficiency and safety, without any human intervention.
Smart pumps, which operate autonomously in order to identify and prevent leakages in the water management infrastructure.
The integration of smart objects within conventional IoT/cloud systems signals a new era for IoT applications, which will be endowed with a host of functionalities that are hardly possible nowadays. AI is one of the main drivers of this new IoT deployment paradigm, as it provides the means for understanding and reasoning over the context of smart objects. While AI functionalities have been around for decades with various forms (e.g., expert systems and fuzzy logic systems), AI systems have not been suitable for supporting smart objects that could act autonomously in open and dynamic environments such as industrial plants and transportation infrastructures.
This is bound to change because of recent advances in AI based on the use of deep learning that employs advanced neural networks and provides human-like reasoning functionalities. During the last couple of years we have witnessed the first tangible demonstrations of such AI capabilities applied in real-life problems. For example, last year, Google’s Alpha AI engine managed to win a Chinese grand-master in the Go game. This signaled a major milestone in AI, as human-like reasoning was used instead of an exhaustive analysis of all possible moves, as was the norm in earlier AI systems in similar settings (e.g., IBM’s Deep Blue computer that beat chess world champion Garry Kasparov back in 1997).
Implications of AI and IoT Convergence for Smart Objects
This convergence of IoT and AI signals a paradigm shift in the way IoT applications are developed, deployed and operated. The main implications of this convergence are:
Changes in IoT architectures: Smart objects operate autonomously and are not subject to the control of a centralized cloud. This requires revisions to the conventional cloud architectures, which should become able to connect to smart objects in an ad hoc fashion towards exchanging state and knowledge about their status and the status of the physical environment.
Expanded use of Edge Computing: Edge computing is already deployed as a means of enabling operations very close to the field, such as fast data processing and real-time control. Smart objects are also likely to connect to the very edge of an IoT deployment, which will lead to an expanded use of the edge computing paradigm.
Killer Applications: AI will enable a whole range of new IoT applications, including some “killer” applications like autonomous driving and predictive maintenance of machines. It will also revolutionize and disrupt existing IoT applications. As a prominent example, the introduction of smart appliances (e.g., washing machines that maintain themselves and order their detergent) in residential environments holds the promise to disrupt the smart home market.
Security and Privacy Challenges: Smart objects increase the volatility, dynamism and complexity of IoT environments, which will lead to new cyber-security challenges. Furthermore, they will enable new ways for compromising citizens’ privacy. Therefore, new ideas for safeguarding security and privacy in this emerging landscape will be needed.
New Standards and Regulations: A new regulatory environment will be needed, given that smart objects might be able to change the status of the physical environment leading to potential damage, losses and liabilities that do not exist nowadays. Likewise, new standards in areas such as safety, security and interoperability will be required.
Market Opportunities: AI and smart objects will offer unprecedented opportunities for new innovative applications and revenue streams. These will not be limited to giant vendors and service providers, but will extend to innovators and SMBs (Small Medium Businesses).
AI is the cornerstone of next generation IoT applications, which will exhibit autonomous behavior and will be subject to decentralized control. These applications will be driven by advances in deep learning and neural networks, which will endow IoT systems with capabilities far beyond conventional data mining and IoT analytics. These trends will be propelled by several other technological advances, including Cyber-Physical Systems (CPS) and blockchain technologies. CPS systems represent a major class of smart objects, which will be increasingly used in industrial environments.
They are the foundation of the fourth industrial revolution through bridging physical processes with digital systems that control and manage industrial processes. Currently CPS systems feature limited intelligence, which is to be enhanced based on the advent and evolution of deep learning. On the other hand, blockchain technology (inspired by the popular Bitcoin cryptocurrency) can provide the means for managing interactions between smart objects, IoT platforms and other IT systems at scale. Blockchains can enable the establishment, auditing and execution of smart contracts between objects and IoT platforms, as a means of controlling the semi-autonomous behavior of the smart object.
This will be a preferred approach to managing smart objects, given that the latter belong to different administrative entities and should be able to interact directly in a scalable fashion, without a need to authenticating themselves against a trusted entity such as a centralized cloud platform.
In terms of possible applications the sky is the limit. AI will enable innovative IoT applications that will boost automation and productivity, while eliminating error prone processes. Are you getting ready for the era of AI in IoT?
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